title: A medical software system for volumetric analysis of cerebral pathologies in magnetic resonance imaging (MRI) data.
abstract: In this contribution, a medical software system for volumetric analysis of different cerebral pathologies in magnetic resonance imaging (MRI) data is presented. The software system is based on a semi-automatic segmentation algorithm and helps to overcome the time-consuming process of volume determination during monitoring of a patient. After imaging, the parameter settings-including a seed point-are set up in the system and an automatic segmentation is performed by a novel graph-based approach. Manually reviewing the result leads to reseeding, adding seed points or an automatic surface mesh generation. The mesh is saved for monitoring the patient and for comparisons with follow-up scans. Based on the mesh, the system performs a voxelization and volume calculation, which leads to diagnosis and therefore further treatment decisions. The overall system has been tested with different cerebral pathologies-glioblastoma multiforme, pituitary adenomas and cerebral aneurysms- and evaluated against manual expert segmentations using the Dice Similarity Coefficient (DSC). Additionally, intra-physician segmentations have been performed to provide a quality measure for the presented system.
authors.affiliation: Department of Neurosurgery, University of Marburg, Baldingerstraße, Marburg, Germany. egger@med.uni-marburg.de
authors.forename: Jan
authors.initials: J
authors.lastname: Egger
authors.forename: Christoph
authors.initials: C
authors.lastname: Kappus
authors.forename: Bernd
authors.initials: B
authors.lastname: Freisleben
authors.forename: Christopher
authors.initials: C
authors.lastname: Nimsky
mesh_terms: D000465:Algorithms; D001927:Brain Diseases / Q000175:diagnosis / Q000503:physiopathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012984:Software